Robust Targets Coverage for Energy Harvesting Wireless Sensor Networks

Energy harvesting wireless sensor networks (EH-WSNs) form the foundation of Internet of Things (IoTs) systems. Energy harvesting nodes can be deployed strategically to monitor one or more targets such as a valuable asset. However, as these nodes rely on ambient energy sources such as solar, they experience random energy arrivals. Consequently, they may exhaust their harvested energy while monitoring a target. Therefore, network operators require a <italic>robust</italic> solution that ensures all targets are monitored continuously over some time period with a given probability. In this paper, we consider three novel robust coverage requirements; each must hold with probability (<inline-formula><tex-math notation="LaTeX">$1-\epsilon$</tex-math></inline-formula>), where <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> is the probability of failures. First, sensor nodes must not expend more than their <italic>total</italic> harvested energy over <inline-formula><tex-math notation="LaTeX">$T$</tex-math></inline-formula> time slots. Second, the energy expenditure of each sensor node must not exceed the energy harvested in <italic>each slot</italic>. Third, the energy expenditure of sensor nodes must not exceed the energy accumulated up to the current slot. We formulate chance-constrained stochastic programs that incorporate these requirements and solve them using the sample average approximation method. We confirm via extensive simulation studies that our programs are capable of computing sensor nodes activation times that meet a given coverage failure probability.

[1]  Alexander Shapiro,et al.  Sample Average Approximation Method for Chance Constrained Programming: Theory and Applications , 2009, J. Optimization Theory and Applications.

[2]  Songwu Lu,et al.  PEAS: a robust energy conserving protocol for long-lived sensor networks , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[3]  Margaret Martonosi,et al.  Hardware design experiences in ZebraNet , 2004, SenSys '04.

[4]  Olivier Berder,et al.  RLMan: An Energy Manager Based on Reinforcement Learning for Energy Harvesting Wireless Sensor Networks , 2018, IEEE Transactions on Green Communications and Networking.

[5]  A. Charnes,et al.  Chance-Constrained Programming , 1959 .

[6]  Liang Huang,et al.  Adaptive Scheduling in Energy Harvesting Sensor Networks for Green Cities , 2018, IEEE Transactions on Industrial Informatics.

[7]  Howie Choset,et al.  Path Planning for Robotic Demining: Robust Sensor-Based Coverage of Unstructured Environments and Probabilistic Methods , 2003, Int. J. Robotics Res..

[8]  Kwan-Wu Chin,et al.  Novel Algorithms for Complete Targets Coverage in Energy Harvesting Wireless Sensor Networks , 2014, IEEE Communications Letters.

[9]  Hiroshi Nakamura,et al.  Adaptive Power Management in Solar Energy Harvesting Sensor Node Using Reinforcement Learning , 2017, ACM Trans. Embed. Comput. Syst..

[10]  Purushottam Kulkarni,et al.  Energy Harvesting Sensor Nodes: Survey and Implications , 2011, IEEE Communications Surveys & Tutorials.

[11]  Bang Wang,et al.  Coverage problems in sensor networks: A survey , 2011, CSUR.

[12]  Alexander Shapiro,et al.  The Sample Average Approximation Method for Stochastic Discrete Optimization , 2002, SIAM J. Optim..

[13]  Matt Welsh,et al.  Deploying a wireless sensor network on an active volcano , 2006, IEEE Internet Computing.

[14]  K. J. Ray Liu,et al.  Data-Driven Stochastic Models and Policies for Energy Harvesting Sensor Communications , 2014, IEEE Journal on Selected Areas in Communications.

[15]  Rong Zheng,et al.  Robust coverage under uncertainty in wireless sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.

[16]  Kwan-Wu Chin,et al.  On Nodes Placement in Energy Harvesting Wireless Sensor Networks for Coverage And Connectivity , 2017, IEEE Transactions on Industrial Informatics.

[17]  Hossam S. Hassanein,et al.  On the robustness of grid-based deployment in wireless sensor networks , 2006, IWCMC '06.

[18]  Ananth Krishnamurthy,et al.  Dynamic node activation in networks of rechargeable sensors , 2005, INFOCOM 2005.

[19]  Timothy Bretl,et al.  Robust coverage by a mobile robot of a planar workspace , 2013, 2013 IEEE International Conference on Robotics and Automation.

[20]  Weifa Liang,et al.  Quality-Aware Target Coverage in Energy Harvesting Sensor Networks , 2015, IEEE Transactions on Emerging Topics in Computing.

[21]  Andrea Zanella,et al.  Internet of Things for Smart Cities , 2014, IEEE Internet of Things Journal.

[22]  Tajana Simunic,et al.  Active sensing platform for wireless structural health monitoring , 2007, IPSN.